• Title/Summary/Keyword: 비정형 객체

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Stereo Images-Based Real-time Object Tracking Using Active Feature Model (능동 특징점 모델을 이용한 스테레오 영상 기반의 실시간 객체 추적)

  • Park, Min-Gyu;Jang, Jong-Whan
    • The KIPS Transactions:PartB
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    • v.16B no.2
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    • pp.109-116
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    • 2009
  • In this thesis, an object tracking method based on the active feature model and the optical flow in stereo images is proposed. We acquired the translation information of object of interest and the features of object by utilizing the geometric information and depth of stereo images. Tracking performance is improved for the occlude object with this information by predicting the movement information of features of the occlude object. Rigid and non-rigid objects are experimented. From the result of experiment, the OOI can be real-time tracked from complicate back ground. Besides, we got the improved result of object tracking in any occlusion state, no matter what it is rigid or non-rigid object.

Development of Quantity Take-off Algorithm for Irregularly Shaped Structures using 3D Object (3D기반 비정형 토목구조물 물량산출 알고리즘 개발)

  • Ha, Cheol-Seok;Moon, So-Yeong;Moon, Hyoun-Seok;Kang, Leen-Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.655-666
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    • 2014
  • Recently, as the appearance and exterior design of the construction structure are highlighted, the irregularly shaped structures are increasing in a construction facility. Many softwares provide a quantity take-off function of 3D object under BIM environment, however, they are focused on the limited function based on the solid modeling method. Because the vast geometric information of the curved surface is difficult to extract in the 3D objects that consist of major changes in vertical section shape as the irregularly shaped structures, it is difficult to express a 3D object as a solid model. On the other hand, the irregularly shaped structures can be expressed in relatively free in the surface model because the surface model consists of points, lines and surfaces. Accordingly, the surface modeling method is suitable for the modeling of large irregularly shaped structures. This study suggests a quantity take-off algorithm for the irregularly shaped structures using the surface modeling approach that is beneficial in the design work of structures. Some case projects are used for verifying the accuracy of the proposed method.

Adaptive Matching Method of Rigid and Deformable Object Image using Statistical Analysis of Matching-pairs (정합 쌍의 통계적 분석을 이용한 정형/비정형 객체 영상의 적응적 정합 방법)

  • Won, In-Su;Yang, Hun-Jun;Jang, Hyeok;Jeong, Dong-Seok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.1
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    • pp.102-110
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    • 2015
  • In this paper, adaptive matching method using the same features for rigid and deformable object images is proposed. Firstly, we determine whether the two images are matched or not using the geometric verification and generate the matching information. Decision boundary which separates deformable matching-pair from non-matching pair is obtained through statistical analysis of matching information. The experimental result shows that the proposed method lowers the computational complexity and increases the matching accuracy compared to the existing method.

A Fire Deteetion System based on YOLOv5 using Web Camera (웹카메라를 이용한 YOLOv5 기반 화재 감지 시스템)

  • Park, Dae-heum;Jang, Si-woong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.69-71
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    • 2022
  • Today, the AI market is very large due to the development of AI. Among them, the most advanced AI is image detection. Thus, there are many object detection models using YOLOv5.However, most object detection in AI is focused on detecting objects that are stereotyped.In order to recognize such unstructured data, the object may be recognized by learning and filtering the object. Therefore, in this paper, a fire monitoring system using YOLOv5 was designed to detect and analyze unstructured data fires and suggest ways to improve the fire object detection model.

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Design and Implementation of Object Storage Engine for Large Multimedia Objects (대용량 멀티미디어 객체를 위한 객체저장엔진의 설계 및 구현)

  • Jin, Ki-Sung;Chang, Jae-Woo
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.4
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    • pp.376-388
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    • 2002
  • Recently, although there are strong requirements to manage multimedia data, there are a few researches on efficient storage and retrieval of multimedia data. In this paper, we design an object storage engine which can store and retrieve various multimedia objects efficiently. For this, we design an object manager for storing a variety of multimedia data and an inverted file manager for indexing unformatted text objects. In addition, we implement the objects storage engine which can support concurrency control and recovery schemes of DBMS by integrating the object manager and the inverted file manager with the SHORE low-level storage system. Finally, we develope a TIROS(Thesis Information Retrieval using Object Storage engine) system in order to verify the usefulness of our object storage engine.

Optimal Camera Placement Leaning of Multiple Cameras for 3D Environment Reconstruction (3차원 환경 복원을 위한 다수 카메라 최적 배치 학습 기법)

  • Kim, Ju-hwan;Jo, Dongsik
    • Smart Media Journal
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    • v.11 no.9
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    • pp.75-80
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    • 2022
  • Recently, research and development on immersive virtual reality(VR) technology to provide a realistic experience is being widely conducted. To provide realistic experience in immersive virtual reality for VR participants, virtual environments should consist of high-realistic environments using 3D reconstruction. In this paper, to acquire 3D information in real space using multiple cameras in the reconstruction process, we propose a novel method of optimal camera placement for accurate reconstruction to minimize distortion of 3D information. Through our approach in this paper, real 3D information can obtain with minimized errors during environment reconstruction, and it is possible to provide a more immersive experience with the created virtual environment.

Block-based Motion Vector Smoothing for Nonrigid Moving Objects (비정형성 등속운동 객체의 움직임 추정을 위한 블록기반 움직임 평활화)

  • Sohn, Young-Wook;Kang, Moon-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.6
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    • pp.47-53
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    • 2007
  • True motion estimation is necessary for deinterlacing, frame-rate conversion, and film judder compensation. There have been several block-based approaches to find true motion vectors by tracing minimum sum-of-absolute-difference (SAD) values by considering spatial and temporal consistency. However, the algorithms cannot find robust motion vectors when the texture of objects is changed. To find the robust motion vectors in the region, a recursive vector selection scheme and an adaptive weighting parameter are proposed. Previous frame vectors are recursively averaged to be utilized for motion error region. The weighting parameter controls fidelity to input vectors and the recursively averaged ones, where the input vectors come from the conventional estimators. If the input vectors are not reliable, then the mean vectors of the previous frame are used for temporal consistency. Experimental results show more robust motion vectors than those of the conventional methods in time-varying texture objects.

Development of a Visual Simulation Tool for Object Behavior Chart based on LOTOS Formalism (객체행위챠트를 위한 LOTOS 정형기법 기반 시각적 시뮬레이션 도구의 개발)

  • Lee, Gwang-Yong;O, Yeong-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.5
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    • pp.595-610
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    • 1999
  • This paper presents a visual simulation tool for verification and validation(V&V) of design implications of the Object Behavior Chart developed in accordance with the existing real-time object's behavior design method. This tool can simulates the dynamic interactions using the executable simulation machine, that is EFSM(Extended Finite State Machine) and can detect various logical and temporal errors in the visual object behavior charts before a concrete implementation is made. For this, a LOTOS prototype specification is automatically generated from the visual Object Behavior Chart, and is translated into an EFSM. This system is implemented in Visual C++ version 4.2 and currently runs on PC Windows 95 environment. For simulation purpose, LOTOS was chosen because of it's excellence in specifying communication protocols. Our research contributes to the support tools for seamlessly integrating methodology-based graphical models and formal-based simulation techniques, and also contributes to the automated V&V of the Visual Models.

Non-Prior Training Active Feature Model-Based Object Tracking for Real-Time Surveillance Systems (실시간 감시 시스템을 위한 사전 무학습 능동 특징점 모델 기반 객체 추적)

  • 김상진;신정호;이성원;백준기
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.23-34
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    • 2004
  • In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

A Conceptual Architecture and its Experimental Validation of CCTV-Video Object Activitization for Tangible Assets of Experts' Visual Knowledge in Smart Factories (고숙련자 공장작업지식 자산화를 위한 CCTV-동영상 객체능동화의 개념적 아키텍처와 실험적 검증)

  • Eun-Bi Cho;Dinh-Lam Pham;Kyung-Hee Sun;Kwanghoon Pio Kim
    • Journal of Internet Computing and Services
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    • v.25 no.2
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    • pp.101-111
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    • 2024
  • In this paper, we propose a concpetual architecture and its implementation approach for contextualizing unstructured CCTV-video frame data into structured XML-video textual data by using the deep-learning neural network models and frameworks. Conclusively, through the conceptual architecture and the implementation approach proposed in this paper, we can eventually realize and implement the so-called sharable working and experiencing knowledge management platforms to be adopted to smart factories in various industries.